Xiang Ao

Iterative Network Pruning with Uncertainty Regularization for Lifelong Sentiment Classification

2021

Lifelong learning capabilities are crucial for sentiment classifiers to process continuous streams of opinioned information on the Web. However, performing lifelong learning is non-trivial for deep neural networks as continually training of incrementally available information …

Along the Time

2022 · Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Recent years have witnessed remarkable progress on knowledge graph embedding (KGE) methods to learn the representations of entities and relations in static knowledge graphs (SKGs). However, knowledge changes over time. In order to represent the …

Selective Fairness in Recommendation via Prompts

2022 · arXiv (Cornell University)

Recommendation fairness has attracted great attention recently. In real-world systems, users usually have multiple sensitive attributes (e.g. age, gender, and occupation), and users may not want their recommendation results influenced by those attributes. Moreover, which …

Gradient-Adaptive Policy Optimization: Towards Multi-Objective Alignment of Large Language Models

2025

Reinforcement Learning from Human Feedback (RLHF) has emerged as a powerful technique for aligning large language models (LLMs) with human preferences.However, effectively aligning LLMs with diverse human preferences remains a significant challenge, particularly when they …

Attention-driven Factor Model for Explainable Personalized Recommendation

2018

Latent Factor Models (LFMs) based on Collaborative Filtering (CF) have been widely applied in many recommendation systems, due to their good performance of prediction accuracy. In addition to users' ratings, auxiliary information such as item …